Advanced planning in vertically integrated supply chains
Date
2011
Authors
Ibrahimov, M.
Mohais, A.
Schellenberg, S.
Michalewicz, Z.
Editors
Bouvry, P.
Gonzalez Velez, H.
Kolodziej, J.
Gonzalez Velez, H.
Kolodziej, J.
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Book chapter
Citation
Intelligent Decision Systems in Large-Scale Distributed Environments, 2011 / Bouvry, P., Gonzalez Velez, H., Kolodziej, J. (ed./s), vol.362, pp.125-148
Statement of Responsibility
Maksud Ibrahimov, Arvind Mohais, Sven Schellenberg, and Zbigniew Michalewicz
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Abstract
During the last few years most production-based businesses have been under enormous pressure to improve their top-line growth and bottom-line savings. As a result, many companies are turning to systems and technologies that can help optimise their supply chain activities and improving short-and long-term demand forecasting. Given the inherent complexities of planning and scheduling in vertically integrated supply chains, many new methods (e.g., ant systems, evolutionary algorithms, fuzzy systems, genetic algorithms, neural networks, rough sets, swarm intelligence, simulated annealing, tabu search-collectively known as "Computational Intelligence" methods) have been introduced into software applications to help manage and and optimise this complexity. In this paper we discuss two realworld applications of advanced planning: one from wine industry and the other-from mining industry. © 2011 Springer-Verlag Berlin Heidelberg.
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© Springer-Verlag Berlin Heidelberg 2011